{"database":"GEO","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE311nnn/GSE311383/"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"omics_type":["Other"],"species":["Homo sapiens"],"gds_type":["Other"],"full_dataset_link":["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE311383"],"repository":["GEO"],"entry_type":["GSE"],"additional_accession":[]},"is_claimable":false,"name":"High-resolution spatial transcriptomics of human liver with VisiumHD","description":"The liver plays a critical role in metabolism and immune function. These crucial functions are diminished in chronic liver diseases, leading to over two million deaths annually worldwide due to liver failure. Single-cell transcriptomics has provided insights into the cellular composition of the liver in health and disease, but is inherently biased due to cell type-specific enrichment and destruction during the single-cell dissociation process. Previous work has highlighted difficulties in capturing specific populations such as cholangiocytes and hepatocytes. Spatial transcriptomics is a promising approach that does not have inherent bias for cell populations and adds important spatial context. Until recently, spatial transcriptomics technologies have only been at a multi-cellular resolution leading to mixed signals from different cell types. The latest spatial transcriptomic technology from 10X Genomics, VisiumHD, enables high-resolution spatial mapping of gene expression in tissue samples, offering a sophisticated platform for exploring the cellular composition of the liver. With a bin width of 2um, it can quantify transcripts at a sub-cellular resolution. Samples from three healthy human liver donors were sequenced and cells were clustered into cell types by integrating spatial transcriptomic data with existing single-cell reference maps. Spatially distinct cell signatures were identified through differential expression analyses and a high-resolution map of the liver was created. This resource provides cell-level and spatially-resolved insights into the cellular and geographical heterogeneity of the liver to serve as a resource for researchers to identify disease-specific spatial signatures and novel therapeutic targets.","dates":{"publication":"2026/04/17"},"accession":"GSE311383","cross_references":{"GSM":["GSM9324328","GSM9324329","GSM9324330"],"GPL":["34281"],"GSE":["311383"],"taxon":["Homo sapiens"]}}